SQL Analyzer
Analyze, lint, and convert SQL dialects using SQLGlot.
mcp-server-sql-analyzer
A Model Context Protocol (MCP) server that provides SQL analysis, linting, and dialect conversion capabilities using SQLGlot.
Overview
The SQL Analyzer MCP server provides tools for analyzing and working with SQL queries. It helps with:
- SQL syntax validation and linting
- Converting queries between different SQL dialects (e.g., MySQL to PostgreSQL)
- Extracting and analyzing table references and dependencies
- Identifying column usage and relationships
- Discovering supported SQL dialects
How Claude Uses This Server
As an AI assistant, this server enhances my ability to help users work with SQL efficiently by:
-
Query Validation: I can instantly validate SQL syntax before suggesting it to users, ensuring I provide correct and dialect-appropriate queries.
-
Dialect Conversion: When users need to migrate queries between different database systems, I can accurately convert the syntax while preserving the query's logic.
-
Code Analysis: The table and column reference analysis helps me understand complex queries, making it easier to explain query structure and suggest optimizations.
-
Compatibility Checking: By knowing the supported dialects and their specific features, I can guide users toward database-specific best practices.
This toolset allows me to provide more accurate and helpful SQL-related assistance while reducing the risk of syntax errors or dialect-specific issues.
Tips
Update your personal preferences in Claude Desktop settings to request that generated SQL is first validated using the lint_sql tool.
Tools
-
lint_sql
- Validates SQL query syntax and returns any errors
- Input:
- sql (string): SQL query to analyze
- dialect (string, optional): SQL dialect (e.g., 'mysql', 'postgres')
- Returns: ParseResult containing:
- is_valid (boolean): Whether the SQL is valid
- message (string): Error message or "No syntax errors"
- position (object, optional): Line and column of error if present
-
transpile_sql
- Converts SQL between different dialects
- Inputs:
- sql (string): SQL statement to transpile
- read_dialect (string): Source SQL dialect
- write_dialect (string): Target SQL dialect
- Returns: TranspileResult containing:
- is_valid (boolean): Whether transpilation succeeded
- message (string): Error message or success confirmation
- sql (string): Transpiled SQL if successful
-
get_all_table_references
- Extracts table and CTE references from SQL
- Inputs:
- sql (string): SQL statement to analyze
- dialect (string, optional): SQL dialect
- Returns: TableReferencesResult containing:
- is_valid (boolean): Whether analysis succeeded
- message (string): Status message
- tables (array): List of table references with type, catalog, database, table name, alias, and fully qualified name
-
get_all_column_references
- Extracts column references with table context
- Inputs:
- sql (string): SQL statement to analyze
- dialect (string, optional): SQL dialect
- Returns: ColumnReferencesResult containing:
- is_valid (boolean): Whether analysis succeeded
- message (string): Status message
- columns (array): List of column references with column name, table name, and fully qualified name
Resources
SQL Dialect Discovery
dialects://all
Returns a list of all supported SQL dialects for use in all tools.
Configuration
Using uvx (recommended)
Add this to your claude_desktop_config.json:
{
"mcpServers": {
"sql-analyzer": {
"command": "uvx",
"args": [
"--from",
"git+https://github.com/j4c0bs/mcp-server-sql-analyzer.git",
"mcp-server-sql-analyzer"
]
}
}
}
Using uv
After cloning this repo, add this to your claude_desktop_config.json:
{
"mcpServers": {
"sql-analyzer": {
"command": "uv",
"args": [
"--directory",
"/path/to/mcp-server-sql-analyzer",
"run",
"mcp-server-sql-analyzer"
]
}
}
}
Development
To run the server in development mode:
# Clone the repository
git clone [email protected]:j4c0bs/mcp-server-sql-analyzer.git
# Run the server
npx @modelcontextprotocol/inspector uv --directory /path/to/mcp-server-sql-analyzer run mcp-server-sql-analyzer
To run unit tests:
uv run pytest .
License
MIT
Related Servers
BioMCP
Connects AI assistants to authoritative biomedical data sources like PubMed and ClinicalTrials.gov, enabling natural language queries.
Google Analytics MCP Server by CData
A read-only MCP server for querying live Google Analytics data using LLMs. Powered by CData.
BigQuery
Access Google BigQuery to understand dataset structures and execute SQL queries.
SimpleDB MCP
A secure MCP server for accessing and exploring relational databases like MySQL, PostgreSQL, Salesforce, and AWS Glue.
Stampchain MCP Server
Interact with Bitcoin Stamps data via the Stampchain API, allowing queries for stamps, collections, and blockchain information.
MCP OpenDART
Access financial data from Korea's OpenDART (Data Analysis, Retrieval and Transfer System) for AI language models.
Databricks MCP Server by CData
A read-only MCP server for Databricks, enabling LLMs to query live data without writing SQL.
Snowflake
Snowflake database integration with read/write capabilities and insight tracking
Epitome
Personal AI memory — gives every AI agent shared, persistent memory of you
MongoDB That Works
A MongoDB MCP server with schema discovery and field validation. Requires a MONGODB_URI environment variable.